176 citations · 179 across the 5 of their papers we have counts for
6 papers
Multi-task Learning for Human Settlement Extent Regression and Local Climate Zone Classification
Chunping Qiu, Lukas Liebel, Lloyd H. Hughes +3
Human Settlement Extent (HSE) and Local Climate Zone (LCZ) maps are both essential sources, e.g., for sustainable urban development and Urban Heat Island (UHI) studies. Remote sens…
A Generalized Multi-Task Learning Approach to Stereo DSM Filtering in Urban Areas
Lukas Liebel, Ksenia Bittner, Marco Körner
City models and height maps of urban areas serve as a valuable data source for numerous applications, such as disaster management or city planning. While this information is not gl…
Weakly Supervised Semantic Segmentation of Satellite Images for Land Cover Mapping -- Challenges and Opportunities
Michael Schmitt, Jonathan Prexl, Patrick Ebel +2
Fully automatic large-scale land cover mapping belongs to the core challenges addressed by the remote sensing community. Usually, the basis of this task is formed by (supervised) m…
MultiDepth: Single-Image Depth Estimation via Multi-Task Regression and Classification
Lukas Liebel, Marco Körner
We introduce MultiDepth, a novel training strategy and convolutional neural network (CNN) architecture that allows approaching single-image depth estimation (SIDE) as a multi-task…
Auxiliary Tasks in Multi-task Learning
Lukas Liebel, Marco Körner
Multi-task convolutional neural networks (CNNs) have shown impressive results for certain combinations of tasks, such as single-image depth estimation (SIDE) and semantic segmentat…
Evaluation of CNN-based Single-Image Depth Estimation Methods
Tobias Koch, Lukas Liebel, Friedrich Fraundorfer +1
While an increasing interest in deep models for single-image depth estimation methods can be observed, established schemes for their evaluation are still limited. We propose a set…